The current stimuli of climate change and rising oil prices have spurred the development of hybrid electric (HEV), and battery electric vehicles (BEV): collectively termed EVs. However, the battery technology needs much development: at the time of writing, the range of a BEV is too low to be practical in many situations. A critical limitation is the sensitivity of batteries to temperature: the heat generated during operation affects their performance and reduces the lifetime.
This study investigates battery cooling using cooling plates: thin rectangular fabrications inserted between battery cells. A coolant pumped through internal channels absorbs heat and transports it away from the battery. Previous studies of liquid heat exchangers have indicated that the geometry of the channels plays a significant role in the performance; however, there is a lack of rigorous numerical optimization applied to EV cooling plates.
By developing a numerical optimization framework utilizing parametric geometry generation and computational fluid dynamics, this research has investigated the characteristics of optimum cooling plate geometry with respect to three objectives: average temperature, temperature uniformity, and coolant pressure drop. By applying each objective separately, improvements of up to 70% have been made compared to a reference design. The influence of boundary conditions on performance and optimum design has been assessed, and multi-objective optimization has investigated the trade-off between competing objective functions.
Although care should be taken when extrapolating the results beyond the geometry and conditions in the study, some general design principles can be proposed. Objectives of average temperature and pressure drop can both be satisfied by a common design with wide cooling channels, but different characteristics are needed for temperature uniformity. Additional assessments have revealed that optimizations of temperature uniformity are especially sensitive to the boundary conditions, whereas the other objective functions are largely insensitive.
The optimization process developed in this work can be applied to any potential cooling plate design and will lead to gains in the targeted performance measure. In doing so, the performance of the EV will be incrementally improved, thereby advancing the day when an EV is not only an environmental choice, but also a practical choice.